Overview

Dataset statistics

Number of variables21
Number of observations114000
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.5 MiB
Average record size in memory161.0 B

Variable types

Numeric13
Categorical7
Boolean1

Alerts

track_id has a high cardinality: 89741 distinct valuesHigh cardinality
artists has a high cardinality: 31437 distinct valuesHigh cardinality
album_name has a high cardinality: 46589 distinct valuesHigh cardinality
track_name has a high cardinality: 73608 distinct valuesHigh cardinality
track_genre has a high cardinality: 114 distinct valuesHigh cardinality
energy is highly overall correlated with loudness and 1 other fieldsHigh correlation
loudness is highly overall correlated with energy and 1 other fieldsHigh correlation
acousticness is highly overall correlated with energy and 1 other fieldsHigh correlation
explicit is highly imbalanced (57.9%)Imbalance
time_signature is highly imbalanced (73.9%)Imbalance
Unnamed: 0 is uniformly distributedUniform
track_id is uniformly distributedUniform
track_genre is uniformly distributedUniform
Unnamed: 0 has unique valuesUnique
popularity has 16020 (14.1%) zerosZeros
key has 13061 (11.5%) zerosZeros
instrumentalness has 38763 (34.0%) zerosZeros

Reproduction

Analysis started2023-12-12 00:09:28.224052
Analysis finished2023-12-12 00:09:41.901325
Duration13.68 seconds
Software versionydata-profiling vv4.1.2
Download configurationconfig.json

Variables

Unnamed: 0
Real number (ℝ)

UNIFORM  UNIQUE 

Distinct114000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56999.5
Minimum0
Maximum113999
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size890.8 KiB
2023-12-12T00:09:41.937247image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5699.95
Q128499.75
median56999.5
Q385499.25
95-th percentile108299.05
Maximum113999
Range113999
Interquartile range (IQR)56999.5

Descriptive statistics

Standard deviation32909.11
Coefficient of variation (CV)0.57735787
Kurtosis-1.2
Mean56999.5
Median Absolute Deviation (MAD)28500
Skewness0
Sum6.497943 × 109
Variance1.0830095 × 109
MonotonicityStrictly increasing
2023-12-12T00:09:41.982606image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1
 
< 0.1%
75997 1
 
< 0.1%
76008 1
 
< 0.1%
76007 1
 
< 0.1%
76006 1
 
< 0.1%
76005 1
 
< 0.1%
76004 1
 
< 0.1%
76003 1
 
< 0.1%
76002 1
 
< 0.1%
76001 1
 
< 0.1%
Other values (113990) 113990
> 99.9%
ValueCountFrequency (%)
0 1
< 0.1%
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
ValueCountFrequency (%)
113999 1
< 0.1%
113998 1
< 0.1%
113997 1
< 0.1%
113996 1
< 0.1%
113995 1
< 0.1%
113994 1
< 0.1%
113993 1
< 0.1%
113992 1
< 0.1%
113991 1
< 0.1%
113990 1
< 0.1%

track_id
Categorical

HIGH CARDINALITY  UNIFORM 

Distinct89741
Distinct (%)78.7%
Missing0
Missing (%)0.0%
Memory size890.8 KiB
6S3JlDAGk3uu3NtZbPnuhS
 
9
2Ey6v4Sekh3Z0RUSISRosD
 
8
2kkvB3RNRzwjFdGhaUA0tz
 
8
5ZsAhuQ24mWHiduaxJqnhW
 
7
08kTa3SL9sV6Iy8KLKtGql
 
7
Other values (89736)
113961 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2508000
Distinct characters62
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73100 ?
Unique (%)64.1%

Sample

1st row5SuOikwiRyPMVoIQDJUgSV
2nd row4qPNDBW1i3p13qLCt0Ki3A
3rd row1iJBSr7s7jYXzM8EGcbK5b
4th row6lfxq3CG4xtTiEg7opyCyx
5th row5vjLSffimiIP26QG5WcN2K

Common Values

ValueCountFrequency (%)
6S3JlDAGk3uu3NtZbPnuhS 9
 
< 0.1%
2Ey6v4Sekh3Z0RUSISRosD 8
 
< 0.1%
2kkvB3RNRzwjFdGhaUA0tz 8
 
< 0.1%
5ZsAhuQ24mWHiduaxJqnhW 7
 
< 0.1%
08kTa3SL9sV6Iy8KLKtGql 7
 
< 0.1%
7tbzfR8ZvZzJEzy6v0d6el 7
 
< 0.1%
0YLSjVxSb5FT1Bo8Tnxr8j 7
 
< 0.1%
4WJTKbNJQ41zXnb84jSWaj 7
 
< 0.1%
2aaClnypAakdAmLw74JXxB 7
 
< 0.1%
2vU6bm5hVF2idVknGzqyPL 7
 
< 0.1%
Other values (89731) 113926
99.9%

Length

2023-12-12T00:09:42.021691image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
6s3jldagk3uu3ntzbpnuhs 9
 
< 0.1%
2kkvb3rnrzwjfdghaua0tz 8
 
< 0.1%
2ey6v4sekh3z0rusisrosd 8
 
< 0.1%
4aqs25f3ywj9tgnnkoqilc 7
 
< 0.1%
5sqkarfxe7uejhtlcthcls 7
 
< 0.1%
6bzwr3epseolvwlblk58il 7
 
< 0.1%
54zcdkbialanv8ihi3xwld 7
 
< 0.1%
4xyiegksljlhpzb3bl6wmp 7
 
< 0.1%
5bi1xqmjk91dseq0bfe0ov 7
 
< 0.1%
5ftfvzslii5zxydnbrtf41 7
 
< 0.1%
Other values (89731) 113926
99.9%

Most occurring characters

ValueCountFrequency (%)
3 53778
 
2.1%
5 53497
 
2.1%
2 53335
 
2.1%
6 53275
 
2.1%
0 53232
 
2.1%
1 53162
 
2.1%
4 53152
 
2.1%
7 50535
 
2.0%
K 39217
 
1.6%
D 39104
 
1.6%
Other values (52) 2005713
80.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1003279
40.0%
Uppercase Letter 1003032
40.0%
Decimal Number 501689
20.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 39217
 
3.9%
D 39104
 
3.9%
G 38991
 
3.9%
A 38963
 
3.9%
W 38756
 
3.9%
E 38755
 
3.9%
X 38726
 
3.9%
B 38719
 
3.9%
I 38705
 
3.9%
R 38684
 
3.9%
Other values (16) 614412
61.3%
Lowercase Letter
ValueCountFrequency (%)
k 39055
 
3.9%
f 38989
 
3.9%
h 38937
 
3.9%
l 38920
 
3.9%
y 38878
 
3.9%
e 38851
 
3.9%
p 38773
 
3.9%
i 38754
 
3.9%
b 38724
 
3.9%
u 38684
 
3.9%
Other values (16) 614714
61.3%
Decimal Number
ValueCountFrequency (%)
3 53778
10.7%
5 53497
10.7%
2 53335
10.6%
6 53275
10.6%
0 53232
10.6%
1 53162
10.6%
4 53152
10.6%
7 50535
10.1%
8 39097
7.8%
9 38626
7.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 2006311
80.0%
Common 501689
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 39217
 
2.0%
D 39104
 
1.9%
k 39055
 
1.9%
G 38991
 
1.9%
f 38989
 
1.9%
A 38963
 
1.9%
h 38937
 
1.9%
l 38920
 
1.9%
y 38878
 
1.9%
e 38851
 
1.9%
Other values (42) 1616406
80.6%
Common
ValueCountFrequency (%)
3 53778
10.7%
5 53497
10.7%
2 53335
10.6%
6 53275
10.6%
0 53232
10.6%
1 53162
10.6%
4 53152
10.6%
7 50535
10.1%
8 39097
7.8%
9 38626
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2508000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 53778
 
2.1%
5 53497
 
2.1%
2 53335
 
2.1%
6 53275
 
2.1%
0 53232
 
2.1%
1 53162
 
2.1%
4 53152
 
2.1%
7 50535
 
2.0%
K 39217
 
1.6%
D 39104
 
1.6%
Other values (52) 2005713
80.0%

artists
Categorical

Distinct31437
Distinct (%)27.6%
Missing1
Missing (%)< 0.1%
Memory size890.8 KiB
The Beatles
 
279
George Jones
 
271
Stevie Wonder
 
236
Linkin Park
 
224
Ella Fitzgerald
 
222
Other values (31432)
112767 

Length

Max length513
Median length322
Mean length16.319354
Min length2

Characters and Unicode

Total characters1860390
Distinct characters712
Distinct categories18 ?
Distinct scripts7 ?
Distinct blocks12 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16767 ?
Unique (%)14.7%

Sample

1st rowGen Hoshino
2nd rowBen Woodward
3rd rowIngrid Michaelson;ZAYN
4th rowKina Grannis
5th rowChord Overstreet

Common Values

ValueCountFrequency (%)
The Beatles 279
 
0.2%
George Jones 271
 
0.2%
Stevie Wonder 236
 
0.2%
Linkin Park 224
 
0.2%
Ella Fitzgerald 222
 
0.2%
Prateek Kuhad 217
 
0.2%
Feid 202
 
0.2%
Chuck Berry 190
 
0.2%
Håkan Hellström 183
 
0.2%
OneRepublic 181
 
0.2%
Other values (31427) 111794
98.1%

Length

2023-12-12T00:09:42.064848image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the 6831
 
2.6%
3126
 
1.2%
de 1133
 
0.4%
los 1066
 
0.4%
of 1034
 
0.4%
dj 738
 
0.3%
george 593
 
0.2%
jones 524
 
0.2%
la 518
 
0.2%
for 457
 
0.2%
Other values (42276) 241844
93.8%

Most occurring characters

ValueCountFrequency (%)
a 164229
 
8.8%
e 148733
 
8.0%
143873
 
7.7%
i 112151
 
6.0%
n 106549
 
5.7%
o 103832
 
5.6%
r 100226
 
5.4%
l 75690
 
4.1%
s 69313
 
3.7%
t 63612
 
3.4%
Other values (702) 772182
41.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1313318
70.6%
Uppercase Letter 338499
 
18.2%
Space Separator 143873
 
7.7%
Other Punctuation 53924
 
2.9%
Decimal Number 5642
 
0.3%
Dash Punctuation 2092
 
0.1%
Other Letter 2008
 
0.1%
Currency Symbol 289
 
< 0.1%
Close Punctuation 181
 
< 0.1%
Open Punctuation 179
 
< 0.1%
Other values (8) 385
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
63
 
3.1%
59
 
2.9%
56
 
2.8%
49
 
2.4%
43
 
2.1%
42
 
2.1%
41
 
2.0%
41
 
2.0%
33
 
1.6%
26
 
1.3%
Other values (453) 1555
77.4%
Lowercase Letter
ValueCountFrequency (%)
a 164229
12.5%
e 148733
11.3%
i 112151
 
8.5%
n 106549
 
8.1%
o 103832
 
7.9%
r 100226
 
7.6%
l 75690
 
5.8%
s 69313
 
5.3%
t 63612
 
4.8%
h 51170
 
3.9%
Other values (102) 317813
24.2%
Uppercase Letter
ValueCountFrequency (%)
S 29141
 
8.6%
A 23980
 
7.1%
M 23977
 
7.1%
B 22899
 
6.8%
T 20678
 
6.1%
C 20253
 
6.0%
D 18520
 
5.5%
R 17533
 
5.2%
L 16695
 
4.9%
P 15667
 
4.6%
Other values (66) 129156
38.2%
Other Punctuation
ValueCountFrequency (%)
; 44293
82.1%
. 3781
 
7.0%
& 2993
 
5.6%
' 1313
 
2.4%
" 566
 
1.0%
! 307
 
0.6%
, 286
 
0.5%
/ 162
 
0.3%
: 155
 
0.3%
? 32
 
0.1%
Other values (9) 36
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 887
15.7%
2 817
14.5%
4 704
12.5%
3 684
12.1%
0 536
9.5%
7 452
8.0%
8 440
7.8%
6 416
7.4%
9 381
6.8%
5 325
 
5.8%
Close Punctuation
ValueCountFrequency (%)
) 147
81.2%
] 24
 
13.3%
5
 
2.8%
3
 
1.7%
} 2
 
1.1%
Math Symbol
ValueCountFrequency (%)
+ 82
52.9%
= 48
31.0%
23
 
14.8%
| 1
 
0.6%
1
 
0.6%
Other Symbol
ValueCountFrequency (%)
6
37.5%
5
31.2%
2
 
12.5%
® 2
 
12.5%
1
 
6.2%
Open Punctuation
ValueCountFrequency (%)
( 147
82.1%
[ 24
 
13.4%
5
 
2.8%
3
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 1999
95.6%
93
 
4.4%
Modifier Letter
ValueCountFrequency (%)
117
98.3%
2
 
1.7%
Final Punctuation
ValueCountFrequency (%)
49
98.0%
1
 
2.0%
Initial Punctuation
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
Space Separator
ValueCountFrequency (%)
143873
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 289
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 20
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 11
100.0%
Other Number
ValueCountFrequency (%)
² 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1645353
88.4%
Common 206570
 
11.1%
Cyrillic 6454
 
0.3%
Han 1291
 
0.1%
Katakana 622
 
< 0.1%
Hiragana 97
 
< 0.1%
Greek 3
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
33
 
2.6%
26
 
2.0%
23
 
1.8%
20
 
1.5%
19
 
1.5%
19
 
1.5%
18
 
1.4%
18
 
1.4%
18
 
1.4%
17
 
1.3%
Other values (380) 1080
83.7%
Latin
ValueCountFrequency (%)
a 164229
 
10.0%
e 148733
 
9.0%
i 112151
 
6.8%
n 106549
 
6.5%
o 103832
 
6.3%
r 100226
 
6.1%
l 75690
 
4.6%
s 69313
 
4.2%
t 63612
 
3.9%
h 51170
 
3.1%
Other values (120) 649848
39.5%
Common
ValueCountFrequency (%)
143873
69.6%
; 44293
 
21.4%
. 3781
 
1.8%
& 2993
 
1.4%
- 1999
 
1.0%
' 1313
 
0.6%
1 887
 
0.4%
2 817
 
0.4%
4 704
 
0.3%
3 684
 
0.3%
Other values (51) 5226
 
2.5%
Cyrillic
ValueCountFrequency (%)
а 816
 
12.6%
о 479
 
7.4%
р 457
 
7.1%
и 429
 
6.6%
е 393
 
6.1%
н 387
 
6.0%
к 279
 
4.3%
в 274
 
4.2%
л 255
 
4.0%
с 227
 
3.5%
Other values (45) 2458
38.1%
Katakana
ValueCountFrequency (%)
63
 
10.1%
59
 
9.5%
56
 
9.0%
49
 
7.9%
43
 
6.9%
42
 
6.8%
41
 
6.6%
41
 
6.6%
19
 
3.1%
18
 
2.9%
Other values (35) 191
30.7%
Hiragana
ValueCountFrequency (%)
10
 
10.3%
8
 
8.2%
7
 
7.2%
6
 
6.2%
6
 
6.2%
6
 
6.2%
6
 
6.2%
5
 
5.2%
5
 
5.2%
4
 
4.1%
Other values (19) 34
35.1%
Greek
ValueCountFrequency (%)
α 2
66.7%
μ 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1842231
99.0%
None 9387
 
0.5%
Cyrillic 6454
 
0.3%
CJK 1289
 
0.1%
Katakana 740
 
< 0.1%
Punctuation 149
 
< 0.1%
Hiragana 97
 
< 0.1%
Math Operators 24
 
< 0.1%
Misc Symbols 6
 
< 0.1%
Letterlike Symbols 5
 
< 0.1%
Other values (2) 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 164229
 
8.9%
e 148733
 
8.1%
143873
 
7.8%
i 112151
 
6.1%
n 106549
 
5.8%
o 103832
 
5.6%
r 100226
 
5.4%
l 75690
 
4.1%
s 69313
 
3.8%
t 63612
 
3.5%
Other values (78) 754023
40.9%
None
ValueCountFrequency (%)
é 1493
15.9%
ã 885
 
9.4%
á 723
 
7.7%
ö 697
 
7.4%
ó 589
 
6.3%
í 570
 
6.1%
ü 502
 
5.3%
ä 419
 
4.5%
ç 362
 
3.9%
ë 296
 
3.2%
Other values (80) 2851
30.4%
Cyrillic
ValueCountFrequency (%)
а 816
 
12.6%
о 479
 
7.4%
р 457
 
7.1%
и 429
 
6.6%
е 393
 
6.1%
н 387
 
6.0%
к 279
 
4.3%
в 274
 
4.2%
л 255
 
4.0%
с 227
 
3.5%
Other values (45) 2458
38.1%
Katakana
ValueCountFrequency (%)
117
15.8%
63
 
8.5%
59
 
8.0%
56
 
7.6%
49
 
6.6%
43
 
5.8%
42
 
5.7%
41
 
5.5%
41
 
5.5%
19
 
2.6%
Other values (37) 210
28.4%
Punctuation
ValueCountFrequency (%)
93
62.4%
49
32.9%
4
 
2.7%
1
 
0.7%
1
 
0.7%
1
 
0.7%
CJK
ValueCountFrequency (%)
33
 
2.6%
26
 
2.0%
23
 
1.8%
20
 
1.6%
19
 
1.5%
19
 
1.5%
18
 
1.4%
18
 
1.4%
18
 
1.4%
17
 
1.3%
Other values (379) 1078
83.6%
Math Operators
ValueCountFrequency (%)
23
95.8%
1
 
4.2%
Hiragana
ValueCountFrequency (%)
10
 
10.3%
8
 
8.2%
7
 
7.2%
6
 
6.2%
6
 
6.2%
6
 
6.2%
6
 
6.2%
5
 
5.2%
5
 
5.2%
4
 
4.1%
Other values (19) 34
35.1%
Misc Symbols
ValueCountFrequency (%)
6
100.0%
Letterlike Symbols
ValueCountFrequency (%)
5
100.0%
Latin Ext Additional
ValueCountFrequency (%)
3
60.0%
2
40.0%
Dingbats
ValueCountFrequency (%)
2
66.7%
1
33.3%

album_name
Categorical

Distinct46589
Distinct (%)40.9%
Missing1
Missing (%)< 0.1%
Memory size890.8 KiB
Alternative Christmas 2022
 
195
Feliz Cumpleaños con Perreo
 
184
Metal
 
143
Halloween con perreito
 
123
Halloween Party 2022
 
115
Other values (46584)
113239 

Length

Max length243
Median length145
Mean length20.116668
Min length1

Characters and Unicode

Total characters2293280
Distinct characters2084
Distinct categories22 ?
Distinct scripts13 ?
Distinct blocks22 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27955 ?
Unique (%)24.5%

Sample

1st rowComedy
2nd rowGhost (Acoustic)
3rd rowTo Begin Again
4th rowCrazy Rich Asians (Original Motion Picture Soundtrack)
5th rowHold On

Common Values

ValueCountFrequency (%)
Alternative Christmas 2022 195
 
0.2%
Feliz Cumpleaños con Perreo 184
 
0.2%
Metal 143
 
0.1%
Halloween con perreito 123
 
0.1%
Halloween Party 2022 115
 
0.1%
The Complete Hank Williams 111
 
0.1%
Fiesta portatil 110
 
0.1%
Frescura y Perreo 106
 
0.1%
Esto me suena a Farra 105
 
0.1%
Perreo en Halloween 103
 
0.1%
Other values (46579) 112704
98.9%

Length

2023-12-12T00:09:42.115865image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the 12029
 
3.1%
9198
 
2.3%
of 5240
 
1.3%
2022 3430
 
0.9%
vol 3257
 
0.8%
christmas 3214
 
0.8%
vivo 3186
 
0.8%
a 3174
 
0.8%
ao 2929
 
0.7%
de 2893
 
0.7%
Other values (35981) 343235
87.6%

Most occurring characters

ValueCountFrequency (%)
277786
 
12.1%
e 184978
 
8.1%
a 142803
 
6.2%
o 138424
 
6.0%
i 127748
 
5.6%
n 106159
 
4.6%
r 105849
 
4.6%
s 96731
 
4.2%
t 96378
 
4.2%
l 79067
 
3.4%
Other values (2074) 937357
40.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1499424
65.4%
Uppercase Letter 364971
 
15.9%
Space Separator 277786
 
12.1%
Decimal Number 50359
 
2.2%
Other Punctuation 32819
 
1.4%
Other Letter 22050
 
1.0%
Close Punctuation 18361
 
0.8%
Open Punctuation 18359
 
0.8%
Dash Punctuation 7237
 
0.3%
Math Symbol 833
 
< 0.1%
Other values (12) 1081
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
399
 
1.8%
375
 
1.7%
291
 
1.3%
287
 
1.3%
255
 
1.2%
235
 
1.1%
223
 
1.0%
210
 
1.0%
193
 
0.9%
179
 
0.8%
Other values (1728) 19403
88.0%
Lowercase Letter
ValueCountFrequency (%)
e 184978
12.3%
a 142803
 
9.5%
o 138424
 
9.2%
i 127748
 
8.5%
n 106159
 
7.1%
r 105849
 
7.1%
s 96731
 
6.5%
t 96378
 
6.4%
l 79067
 
5.3%
u 52306
 
3.5%
Other values (128) 368981
24.6%
Uppercase Letter
ValueCountFrequency (%)
S 30218
 
8.3%
T 27866
 
7.6%
A 26171
 
7.2%
M 22698
 
6.2%
C 22365
 
6.1%
P 19741
 
5.4%
R 19064
 
5.2%
B 18069
 
5.0%
E 18023
 
4.9%
D 17769
 
4.9%
Other values (91) 142987
39.2%
Other Punctuation
ValueCountFrequency (%)
. 9198
28.0%
' 5195
15.8%
, 4878
14.9%
: 4462
13.6%
& 2559
 
7.8%
/ 2109
 
6.4%
" 1606
 
4.9%
! 1249
 
3.8%
? 500
 
1.5%
# 247
 
0.8%
Other values (13) 816
 
2.5%
Nonspacing Mark
ValueCountFrequency (%)
57
51.4%
̆ 13
 
11.7%
́ 12
 
10.8%
8
 
7.2%
̈ 6
 
5.4%
4
 
3.6%
3
 
2.7%
̀ 2
 
1.8%
2
 
1.8%
1
 
0.9%
Other values (3) 3
 
2.7%
Decimal Number
ValueCountFrequency (%)
2 18813
37.4%
0 12475
24.8%
1 6993
 
13.9%
9 2621
 
5.2%
3 2418
 
4.8%
5 1894
 
3.8%
4 1473
 
2.9%
7 1297
 
2.6%
6 1213
 
2.4%
8 1162
 
2.3%
Math Symbol
ValueCountFrequency (%)
+ 301
36.1%
~ 271
32.5%
| 86
 
10.3%
> 69
 
8.3%
< 66
 
7.9%
= 20
 
2.4%
10
 
1.2%
× 7
 
0.8%
÷ 2
 
0.2%
1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 17382
94.7%
[ 810
 
4.4%
54
 
0.3%
51
 
0.3%
43
 
0.2%
10
 
0.1%
{ 8
 
< 0.1%
1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 17381
94.7%
] 813
 
4.4%
54
 
0.3%
51
 
0.3%
43
 
0.2%
10
 
0.1%
} 8
 
< 0.1%
1
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
® 20
32.8%
° 17
27.9%
14
23.0%
4
 
6.6%
2
 
3.3%
2
 
3.3%
1
 
1.6%
1
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 6981
96.5%
185
 
2.6%
60
 
0.8%
6
 
0.1%
4
 
0.1%
1
 
< 0.1%
Modifier Symbol
ValueCountFrequency (%)
´ 30
90.9%
` 2
 
6.1%
˚ 1
 
3.0%
Letter Number
ValueCountFrequency (%)
15
75.0%
4
 
20.0%
1
 
5.0%
Spacing Mark
ValueCountFrequency (%)
5
55.6%
3
33.3%
1
 
11.1%
Modifier Letter
ValueCountFrequency (%)
396
95.2%
20
 
4.8%
Final Punctuation
ValueCountFrequency (%)
205
81.7%
46
 
18.3%
Initial Punctuation
ValueCountFrequency (%)
54
90.0%
6
 
10.0%
Format
ValueCountFrequency (%)
14
87.5%
2
 
12.5%
Space Separator
ValueCountFrequency (%)
277786
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 72
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 31
100.0%
Other Number
ValueCountFrequency (%)
² 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1845383
80.5%
Common 406675
 
17.7%
Cyrillic 18965
 
0.8%
Han 13340
 
0.6%
Katakana 5077
 
0.2%
Hiragana 3518
 
0.2%
Inherited 102
 
< 0.1%
Greek 80
 
< 0.1%
Hangul 47
 
< 0.1%
Arabic 44
 
< 0.1%
Other values (3) 49
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
291
 
2.2%
235
 
1.8%
193
 
1.4%
134
 
1.0%
134
 
1.0%
132
 
1.0%
124
 
0.9%
117
 
0.9%
111
 
0.8%
109
 
0.8%
Other values (1537) 11760
88.2%
Latin
ValueCountFrequency (%)
e 184978
 
10.0%
a 142803
 
7.7%
o 138424
 
7.5%
i 127748
 
6.9%
n 106159
 
5.8%
r 105849
 
5.7%
s 96731
 
5.2%
t 96378
 
5.2%
l 79067
 
4.3%
u 52306
 
2.8%
Other values (144) 714940
38.7%
Common
ValueCountFrequency (%)
277786
68.3%
2 18813
 
4.6%
( 17382
 
4.3%
) 17381
 
4.3%
0 12475
 
3.1%
. 9198
 
2.3%
1 6993
 
1.7%
- 6981
 
1.7%
' 5195
 
1.3%
, 4878
 
1.2%
Other values (77) 29593
 
7.3%
Katakana
ValueCountFrequency (%)
399
 
7.9%
287
 
5.7%
255
 
5.0%
210
 
4.1%
179
 
3.5%
169
 
3.3%
166
 
3.3%
160
 
3.2%
151
 
3.0%
145
 
2.9%
Other values (68) 2956
58.2%
Hiragana
ValueCountFrequency (%)
375
 
10.7%
223
 
6.3%
176
 
5.0%
155
 
4.4%
143
 
4.1%
134
 
3.8%
127
 
3.6%
119
 
3.4%
110
 
3.1%
106
 
3.0%
Other values (60) 1850
52.6%
Cyrillic
ValueCountFrequency (%)
а 1613
 
8.5%
е 1611
 
8.5%
о 1439
 
7.6%
н 1314
 
6.9%
с 1289
 
6.8%
и 1226
 
6.5%
р 896
 
4.7%
т 894
 
4.7%
к 749
 
3.9%
л 727
 
3.8%
Other values (53) 7207
38.0%
Greek
ValueCountFrequency (%)
φ 27
33.8%
α 6
 
7.5%
Ξ 5
 
6.2%
ς 4
 
5.0%
μ 3
 
3.8%
Ψ 3
 
3.8%
ε 2
 
2.5%
ή 2
 
2.5%
τ 2
 
2.5%
ό 2
 
2.5%
Other values (16) 24
30.0%
Malayalam
ValueCountFrequency (%)
5
13.2%
4
10.5%
4
10.5%
3
 
7.9%
3
 
7.9%
3
 
7.9%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%
Other values (8) 8
21.1%
Hangul
ValueCountFrequency (%)
8
17.0%
6
12.8%
4
8.5%
4
8.5%
4
8.5%
4
8.5%
4
8.5%
2
 
4.3%
2
 
4.3%
2
 
4.3%
Other values (6) 7
14.9%
Arabic
ValueCountFrequency (%)
ا 8
18.2%
ی 6
13.6%
چ 4
9.1%
ه 4
9.1%
و 4
9.1%
ت 4
9.1%
ر 4
9.1%
ک 4
9.1%
ل 4
9.1%
م 2
 
4.5%
Inherited
ValueCountFrequency (%)
57
55.9%
̆ 13
 
12.7%
́ 12
 
11.8%
8
 
7.8%
̈ 6
 
5.9%
̀ 2
 
2.0%
2
 
2.0%
̊ 1
 
1.0%
̃ 1
 
1.0%
Thai
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Devanagari
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2236463
97.5%
Cyrillic 18965
 
0.8%
None 14518
 
0.6%
CJK 13319
 
0.6%
Katakana 5702
 
0.2%
Hiragana 3583
 
0.2%
Punctuation 455
 
< 0.1%
Hangul 47
 
< 0.1%
Arabic 44
 
< 0.1%
Malayalam 38
 
< 0.1%
Other values (12) 146
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
277786
 
12.4%
e 184978
 
8.3%
a 142803
 
6.4%
o 138424
 
6.2%
i 127748
 
5.7%
n 106159
 
4.7%
r 105849
 
4.7%
s 96731
 
4.3%
t 96378
 
4.3%
l 79067
 
3.5%
Other values (83) 880540
39.4%
Cyrillic
ValueCountFrequency (%)
а 1613
 
8.5%
е 1611
 
8.5%
о 1439
 
7.6%
н 1314
 
6.9%
с 1289
 
6.8%
и 1226
 
6.5%
р 896
 
4.7%
т 894
 
4.7%
к 749
 
3.9%
л 727
 
3.8%
Other values (53) 7207
38.0%
None
ValueCountFrequency (%)
ó 1193
 
8.2%
ã 1163
 
8.0%
á 1148
 
7.9%
é 1070
 
7.4%
ç 845
 
5.8%
ú 836
 
5.8%
ñ 745
 
5.1%
ü 728
 
5.0%
í 718
 
4.9%
ı 672
 
4.6%
Other values (132) 5400
37.2%
Katakana
ValueCountFrequency (%)
399
 
7.0%
396
 
6.9%
287
 
5.0%
255
 
4.5%
229
 
4.0%
210
 
3.7%
179
 
3.1%
169
 
3.0%
166
 
2.9%
160
 
2.8%
Other values (70) 3252
57.0%
Hiragana
ValueCountFrequency (%)
375
 
10.5%
223
 
6.2%
176
 
4.9%
155
 
4.3%
143
 
4.0%
134
 
3.7%
127
 
3.5%
119
 
3.3%
110
 
3.1%
106
 
3.0%
Other values (62) 1915
53.4%
CJK
ValueCountFrequency (%)
291
 
2.2%
235
 
1.8%
193
 
1.4%
134
 
1.0%
134
 
1.0%
132
 
1.0%
124
 
0.9%
117
 
0.9%
111
 
0.8%
109
 
0.8%
Other values (1535) 11739
88.1%
Punctuation
ValueCountFrequency (%)
205
45.1%
60
 
13.2%
54
 
11.9%
48
 
10.5%
46
 
10.1%
14
 
3.1%
6
 
1.3%
6
 
1.3%
6
 
1.3%
4
 
0.9%
Other values (3) 6
 
1.3%
IPA Ext
ValueCountFrequency (%)
ə 20
100.0%
Number Forms
ValueCountFrequency (%)
15
78.9%
4
 
21.1%
Misc Symbols
ValueCountFrequency (%)
14
70.0%
4
 
20.0%
2
 
10.0%
Diacriticals
ValueCountFrequency (%)
̆ 13
37.1%
́ 12
34.3%
̈ 6
17.1%
̀ 2
 
5.7%
̊ 1
 
2.9%
̃ 1
 
2.9%
Math Operators
ValueCountFrequency (%)
10
90.9%
1
 
9.1%
Hangul
ValueCountFrequency (%)
8
17.0%
6
12.8%
4
8.5%
4
8.5%
4
8.5%
4
8.5%
4
8.5%
2
 
4.3%
2
 
4.3%
2
 
4.3%
Other values (6) 7
14.9%
Arabic
ValueCountFrequency (%)
ا 8
18.2%
ی 6
13.6%
چ 4
9.1%
ه 4
9.1%
و 4
9.1%
ت 4
9.1%
ر 4
9.1%
ک 4
9.1%
ل 4
9.1%
م 2
 
4.5%
Devanagari
ValueCountFrequency (%)
6
100.0%
Latin Ext Additional
ValueCountFrequency (%)
6
26.1%
6
26.1%
3
13.0%
2
 
8.7%
2
 
8.7%
2
 
8.7%
2
 
8.7%
Malayalam
ValueCountFrequency (%)
5
13.2%
4
10.5%
4
10.5%
3
 
7.9%
3
 
7.9%
3
 
7.9%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%
Other values (8) 8
21.1%
Dingbats
ValueCountFrequency (%)
2
66.7%
1
33.3%
VS
ValueCountFrequency (%)
2
100.0%
Geometric Shapes
ValueCountFrequency (%)
1
100.0%
Thai
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Modifier Letters
ValueCountFrequency (%)
˚ 1
100.0%

track_name
Categorical

Distinct73608
Distinct (%)64.6%
Missing1
Missing (%)< 0.1%
Memory size890.8 KiB
Run Rudolph Run
 
151
Halloween
 
88
Frosty The Snowman
 
81
Little Saint Nick - 1991 Remix
 
76
Last Last
 
75
Other values (73603)
113528 

Length

Max length511
Median length146
Mean length17.994684
Min length1

Characters and Unicode

Total characters2051376
Distinct characters2417
Distinct categories23 ?
Distinct scripts13 ?
Distinct blocks25 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55711 ?
Unique (%)48.9%

Sample

1st rowComedy
2nd rowGhost - Acoustic
3rd rowTo Begin Again
4th rowCan't Help Falling In Love
5th rowHold On

Common Values

ValueCountFrequency (%)
Run Rudolph Run 151
 
0.1%
Halloween 88
 
0.1%
Frosty The Snowman 81
 
0.1%
Little Saint Nick - 1991 Remix 76
 
0.1%
Last Last 75
 
0.1%
Christmas Time 72
 
0.1%
CÓMO SE SIENTE - Remix 64
 
0.1%
Sleigh Ride 61
 
0.1%
RUMBATÓN 60
 
0.1%
X ÚLTIMA VEZ 58
 
0.1%
Other values (73598) 113213
99.3%

Length

2023-12-12T00:09:42.167175image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
19654
 
5.1%
the 9471
 
2.5%
you 4292
 
1.1%
me 3716
 
1.0%
a 3696
 
1.0%
of 3605
 
0.9%
i 3409
 
0.9%
in 3180
 
0.8%
vivo 3158
 
0.8%
remix 2984
 
0.8%
Other values (50550) 328614
85.2%

Most occurring characters

ValueCountFrequency (%)
271780
 
13.2%
e 174853
 
8.5%
a 136251
 
6.6%
o 122444
 
6.0%
i 109433
 
5.3%
n 94021
 
4.6%
r 92079
 
4.5%
t 81895
 
4.0%
s 67733
 
3.3%
l 63149
 
3.1%
Other values (2407) 837738
40.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1322573
64.5%
Uppercase Letter 342166
 
16.7%
Space Separator 271780
 
13.2%
Other Punctuation 30401
 
1.5%
Other Letter 23202
 
1.1%
Decimal Number 21475
 
1.0%
Dash Punctuation 17861
 
0.9%
Open Punctuation 10046
 
0.5%
Close Punctuation 10043
 
0.5%
Modifier Letter 616
 
< 0.1%
Other values (13) 1213
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
486
 
2.1%
431
 
1.9%
344
 
1.5%
305
 
1.3%
282
 
1.2%
236
 
1.0%
230
 
1.0%
219
 
0.9%
217
 
0.9%
216
 
0.9%
Other values (2056) 20236
87.2%
Lowercase Letter
ValueCountFrequency (%)
e 174853
13.2%
a 136251
10.3%
o 122444
 
9.3%
i 109433
 
8.3%
n 94021
 
7.1%
r 92079
 
7.0%
t 81895
 
6.2%
s 67733
 
5.1%
l 63149
 
4.8%
u 47642
 
3.6%
Other values (135) 333073
25.2%
Uppercase Letter
ValueCountFrequency (%)
S 27792
 
8.1%
T 25354
 
7.4%
M 24538
 
7.2%
A 24257
 
7.1%
L 18809
 
5.5%
C 18140
 
5.3%
R 17783
 
5.2%
D 17415
 
5.1%
B 16803
 
4.9%
I 15197
 
4.4%
Other values (84) 136078
39.8%
Other Punctuation
ValueCountFrequency (%)
. 7423
24.4%
' 6630
21.8%
, 4558
15.0%
" 3525
11.6%
/ 2376
 
7.8%
: 1968
 
6.5%
& 1478
 
4.9%
! 1110
 
3.7%
? 780
 
2.6%
169
 
0.6%
Other values (11) 384
 
1.3%
Nonspacing Mark
ValueCountFrequency (%)
́ 50
36.0%
26
18.7%
̃ 14
 
10.1%
̧ 12
 
8.6%
̈ 9
 
6.5%
̂ 7
 
5.0%
5
 
3.6%
̆ 5
 
3.6%
̊ 3
 
2.2%
2
 
1.4%
Other values (5) 6
 
4.3%
Decimal Number
ValueCountFrequency (%)
0 4889
22.8%
2 4797
22.3%
1 3921
18.3%
9 2029
9.4%
3 1105
 
5.1%
4 1105
 
5.1%
5 1068
 
5.0%
8 887
 
4.1%
7 859
 
4.0%
6 815
 
3.8%
Math Symbol
ValueCountFrequency (%)
+ 90
36.6%
~ 52
21.1%
| 51
20.7%
= 20
 
8.1%
> 16
 
6.5%
< 12
 
4.9%
2
 
0.8%
1
 
0.4%
1
 
0.4%
× 1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 9568
95.2%
[ 358
 
3.6%
77
 
0.8%
35
 
0.3%
3
 
< 0.1%
2
 
< 0.1%
{ 1
 
< 0.1%
1
 
< 0.1%
1
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
11
28.9%
° 11
28.9%
8
21.1%
® 2
 
5.3%
2
 
5.3%
1
 
2.6%
1
 
2.6%
1
 
2.6%
1
 
2.6%
Close Punctuation
ValueCountFrequency (%)
) 9567
95.3%
] 357
 
3.6%
77
 
0.8%
35
 
0.3%
3
 
< 0.1%
2
 
< 0.1%
} 1
 
< 0.1%
1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 17711
99.2%
112
 
0.6%
26
 
0.1%
10
 
0.1%
2
 
< 0.1%
Modifier Symbol
ValueCountFrequency (%)
´ 62
80.5%
` 13
 
16.9%
˙ 1
 
1.3%
^ 1
 
1.3%
Final Punctuation
ValueCountFrequency (%)
415
88.1%
46
 
9.8%
» 10
 
2.1%
Initial Punctuation
ValueCountFrequency (%)
76
55.1%
52
37.7%
« 10
 
7.2%
Format
ValueCountFrequency (%)
8
80.0%
1
 
10.0%
 1
 
10.0%
Modifier Letter
ValueCountFrequency (%)
603
97.9%
13
 
2.1%
Currency Symbol
ValueCountFrequency (%)
$ 56
98.2%
1
 
1.8%
Other Number
ValueCountFrequency (%)
½ 2
66.7%
² 1
33.3%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
271780
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 29
100.0%
Private Use
ValueCountFrequency (%)
1
100.0%
Control
ValueCountFrequency (%)
‚ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1652883
80.6%
Common 363278
 
17.7%
Han 13773
 
0.7%
Cyrillic 11823
 
0.6%
Katakana 5060
 
0.2%
Hiragana 4279
 
0.2%
Inherited 138
 
< 0.1%
Hangul 66
 
< 0.1%
Greek 42
 
< 0.1%
Arabic 26
 
< 0.1%
Other values (3) 8
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
344
 
2.5%
236
 
1.7%
230
 
1.7%
207
 
1.5%
204
 
1.5%
201
 
1.5%
158
 
1.1%
131
 
1.0%
122
 
0.9%
115
 
0.8%
Other values (1836) 11825
85.9%
Latin
ValueCountFrequency (%)
e 174853
 
10.6%
a 136251
 
8.2%
o 122444
 
7.4%
i 109433
 
6.6%
n 94021
 
5.7%
r 92079
 
5.6%
t 81895
 
5.0%
s 67733
 
4.1%
l 63149
 
3.8%
u 47642
 
2.9%
Other values (144) 663383
40.1%
Common
ValueCountFrequency (%)
271780
74.8%
- 17711
 
4.9%
( 9568
 
2.6%
) 9567
 
2.6%
. 7423
 
2.0%
' 6630
 
1.8%
0 4889
 
1.3%
2 4797
 
1.3%
, 4558
 
1.3%
1 3921
 
1.1%
Other values (82) 22434
 
6.2%
Katakana
ValueCountFrequency (%)
431
 
8.5%
305
 
6.0%
219
 
4.3%
216
 
4.3%
204
 
4.0%
165
 
3.3%
147
 
2.9%
141
 
2.8%
133
 
2.6%
132
 
2.6%
Other values (69) 2967
58.6%
Hiragana
ValueCountFrequency (%)
486
 
11.4%
282
 
6.6%
217
 
5.1%
165
 
3.9%
135
 
3.2%
132
 
3.1%
129
 
3.0%
122
 
2.9%
118
 
2.8%
111
 
2.6%
Other values (63) 2382
55.7%
Cyrillic
ValueCountFrequency (%)
а 1031
 
8.7%
о 988
 
8.4%
е 903
 
7.6%
и 703
 
5.9%
н 676
 
5.7%
р 584
 
4.9%
т 536
 
4.5%
л 521
 
4.4%
с 495
 
4.2%
к 419
 
3.5%
Other values (53) 4967
42.0%
Hangul
ValueCountFrequency (%)
3
 
4.5%
3
 
4.5%
3
 
4.5%
2
 
3.0%
2
 
3.0%
2
 
3.0%
2
 
3.0%
2
 
3.0%
2
 
3.0%
2
 
3.0%
Other values (38) 43
65.2%
Greek
ValueCountFrequency (%)
ο 4
 
9.5%
τ 3
 
7.1%
ι 3
 
7.1%
Ψ 3
 
7.1%
Σ 3
 
7.1%
Ξ 3
 
7.1%
Χ 3
 
7.1%
ε 2
 
4.8%
φ 2
 
4.8%
Δ 1
 
2.4%
Other values (15) 15
35.7%
Arabic
ValueCountFrequency (%)
د 4
15.4%
م 3
11.5%
ر 3
11.5%
ع 2
 
7.7%
ن 2
 
7.7%
ا 2
 
7.7%
ه 1
 
3.8%
ق 1
 
3.8%
ب 1
 
3.8%
س 1
 
3.8%
Other values (6) 6
23.1%
Inherited
ValueCountFrequency (%)
́ 50
36.2%
26
18.8%
̃ 14
 
10.1%
̧ 12
 
8.7%
̈ 9
 
6.5%
̂ 7
 
5.1%
5
 
3.6%
̆ 5
 
3.6%
̊ 3
 
2.2%
2
 
1.4%
Other values (4) 5
 
3.6%
Thai
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Devanagari
ValueCountFrequency (%)
2
100.0%
Unknown
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000174
97.5%
None 14540
 
0.7%
CJK 13759
 
0.7%
Cyrillic 11823
 
0.6%
Katakana 5832
 
0.3%
Hiragana 4310
 
0.2%
Punctuation 676
 
< 0.1%
Diacriticals 104
 
< 0.1%
Hangul 66
 
< 0.1%
Arabic 26
 
< 0.1%
Other values (15) 66
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
271780
 
13.6%
e 174853
 
8.7%
a 136251
 
6.8%
o 122444
 
6.1%
i 109433
 
5.5%
n 94021
 
4.7%
r 92079
 
4.6%
t 81895
 
4.1%
s 67733
 
3.4%
l 63149
 
3.2%
Other values (84) 786536
39.3%
None
ValueCountFrequency (%)
é 1544
 
10.6%
ã 1400
 
9.6%
á 1111
 
7.6%
ó 1100
 
7.6%
í 896
 
6.2%
ç 843
 
5.8%
ä 663
 
4.6%
ê 604
 
4.2%
ı 588
 
4.0%
ü 577
 
4.0%
Other values (137) 5214
35.9%
Cyrillic
ValueCountFrequency (%)
а 1031
 
8.7%
о 988
 
8.4%
е 903
 
7.6%
и 703
 
5.9%
н 676
 
5.7%
р 584
 
4.9%
т 536
 
4.5%
л 521
 
4.4%
с 495
 
4.2%
к 419
 
3.5%
Other values (53) 4967
42.0%
Katakana
ValueCountFrequency (%)
603
 
10.3%
431
 
7.4%
305
 
5.2%
219
 
3.8%
216
 
3.7%
204
 
3.5%
169
 
2.9%
165
 
2.8%
147
 
2.5%
141
 
2.4%
Other values (71) 3232
55.4%
Hiragana
ValueCountFrequency (%)
486
 
11.3%
282
 
6.5%
217
 
5.0%
165
 
3.8%
135
 
3.1%
132
 
3.1%
129
 
3.0%
122
 
2.8%
118
 
2.7%
111
 
2.6%
Other values (65) 2413
56.0%
Punctuation
ValueCountFrequency (%)
415
61.4%
76
 
11.2%
52
 
7.7%
46
 
6.8%
39
 
5.8%
26
 
3.8%
10
 
1.5%
8
 
1.2%
2
 
0.3%
1
 
0.1%
CJK
ValueCountFrequency (%)
344
 
2.5%
236
 
1.7%
230
 
1.7%
207
 
1.5%
204
 
1.5%
201
 
1.5%
158
 
1.1%
131
 
1.0%
122
 
0.9%
115
 
0.8%
Other values (1834) 11811
85.8%
Diacriticals
ValueCountFrequency (%)
́ 50
48.1%
̃ 14
 
13.5%
̧ 12
 
11.5%
̈ 9
 
8.7%
̂ 7
 
6.7%
̆ 5
 
4.8%
̊ 3
 
2.9%
̀ 2
 
1.9%
̌ 1
 
1.0%
̇ 1
 
1.0%
Misc Symbols
ValueCountFrequency (%)
11
55.0%
8
40.0%
1
 
5.0%
IPA Ext
ValueCountFrequency (%)
ə 10
100.0%
Arabic
ValueCountFrequency (%)
د 4
15.4%
م 3
11.5%
ر 3
11.5%
ع 2
 
7.7%
ن 2
 
7.7%
ا 2
 
7.7%
ه 1
 
3.8%
ق 1
 
3.8%
ب 1
 
3.8%
س 1
 
3.8%
Other values (6) 6
23.1%
Hangul
ValueCountFrequency (%)
3
 
4.5%
3
 
4.5%
3
 
4.5%
2
 
3.0%
2
 
3.0%
2
 
3.0%
2
 
3.0%
2
 
3.0%
2
 
3.0%
2
 
3.0%
Other values (38) 43
65.2%
Latin Ext Additional
ValueCountFrequency (%)
3
23.1%
2
15.4%
2
15.4%
2
15.4%
2
15.4%
2
15.4%
Devanagari
ValueCountFrequency (%)
2
100.0%
Number Forms
ValueCountFrequency (%)
2
100.0%
VS
ValueCountFrequency (%)
2
100.0%
Dingbats
ValueCountFrequency (%)
2
100.0%
Arrows
ValueCountFrequency (%)
2
100.0%
Geometric Shapes
ValueCountFrequency (%)
1
50.0%
1
50.0%
Thai
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Misc Technical
ValueCountFrequency (%)
1
100.0%
Currency Symbols
ValueCountFrequency (%)
1
100.0%
PUA
ValueCountFrequency (%)
1
100.0%
Math Operators
ValueCountFrequency (%)
1
50.0%
1
50.0%
Modifier Letters
ValueCountFrequency (%)
˙ 1
100.0%

popularity
Real number (ℝ)

Distinct101
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.238535
Minimum0
Maximum100
Zeros16020
Zeros (%)14.1%
Negative0
Negative (%)0.0%
Memory size890.8 KiB
2023-12-12T00:09:42.214528image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q117
median35
Q350
95-th percentile69
Maximum100
Range100
Interquartile range (IQR)33

Descriptive statistics

Standard deviation22.305078
Coefficient of variation (CV)0.67106082
Kurtosis-0.92775532
Mean33.238535
Median Absolute Deviation (MAD)16
Skewness0.046402516
Sum3789193
Variance497.51653
MonotonicityNot monotonic
2023-12-12T00:09:42.258027image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16020
 
14.1%
22 2354
 
2.1%
21 2344
 
2.1%
44 2288
 
2.0%
1 2140
 
1.9%
23 2117
 
1.9%
20 2110
 
1.9%
43 2073
 
1.8%
45 2004
 
1.8%
41 1996
 
1.8%
Other values (91) 78554
68.9%
ValueCountFrequency (%)
0 16020
14.1%
1 2140
 
1.9%
2 1036
 
0.9%
3 585
 
0.5%
4 389
 
0.3%
5 599
 
0.5%
6 426
 
0.4%
7 465
 
0.4%
8 544
 
0.5%
9 525
 
0.5%
ValueCountFrequency (%)
100 2
 
< 0.1%
99 1
 
< 0.1%
98 7
< 0.1%
97 8
< 0.1%
96 7
< 0.1%
95 5
< 0.1%
94 7
< 0.1%
93 12
< 0.1%
92 9
< 0.1%
91 10
< 0.1%

duration_ms
Real number (ℝ)

Distinct50697
Distinct (%)44.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean228029.15
Minimum0
Maximum5237295
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size890.8 KiB
2023-12-12T00:09:42.300682image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile116920
Q1174066
median212906
Q3261506
95-th percentile387167.1
Maximum5237295
Range5237295
Interquartile range (IQR)87440

Descriptive statistics

Standard deviation107297.71
Coefficient of variation (CV)0.47054384
Kurtosis354.95242
Mean228029.15
Median Absolute Deviation (MAD)42760
Skewness11.195181
Sum2.5995323 × 1010
Variance1.1512799 × 1010
MonotonicityNot monotonic
2023-12-12T00:09:42.344124image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
162897 146
 
0.1%
180000 104
 
0.1%
192000 91
 
0.1%
240000 84
 
0.1%
118840 76
 
0.1%
172342 75
 
0.1%
227520 71
 
0.1%
131733 70
 
0.1%
243057 66
 
0.1%
175986 63
 
0.1%
Other values (50687) 113154
99.3%
ValueCountFrequency (%)
0 1
< 0.1%
8586 1
< 0.1%
13386 1
< 0.1%
15800 1
< 0.1%
17453 1
< 0.1%
17826 2
< 0.1%
21120 1
< 0.1%
21240 1
< 0.1%
22266 1
< 0.1%
23506 2
< 0.1%
ValueCountFrequency (%)
5237295 1
< 0.1%
4789026 2
< 0.1%
4730302 1
< 0.1%
4563897 1
< 0.1%
4447520 1
< 0.1%
4339826 1
< 0.1%
4334721 1
< 0.1%
4246206 1
< 0.1%
4120258 1
< 0.1%
3876276 2
< 0.1%

explicit
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size111.5 KiB
False
104253 
True
 
9747
ValueCountFrequency (%)
False 104253
91.5%
True 9747
 
8.6%
2023-12-12T00:09:42.386322image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

danceability
Real number (ℝ)

Distinct1174
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.56680007
Minimum0
Maximum0.985
Zeros157
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size890.8 KiB
2023-12-12T00:09:42.421736image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.25
Q10.456
median0.58
Q30.695
95-th percentile0.824
Maximum0.985
Range0.985
Interquartile range (IQR)0.239

Descriptive statistics

Standard deviation0.17354217
Coefficient of variation (CV)0.30617882
Kurtosis-0.18450245
Mean0.56680007
Median Absolute Deviation (MAD)0.119
Skewness-0.39949663
Sum64615.207
Variance0.030116886
MonotonicityNot monotonic
2023-12-12T00:09:42.465651image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.647 431
 
0.4%
0.609 357
 
0.3%
0.579 347
 
0.3%
0.685 335
 
0.3%
0.602 334
 
0.3%
0.524 317
 
0.3%
0.689 315
 
0.3%
0.598 312
 
0.3%
0.607 307
 
0.3%
0.626 306
 
0.3%
Other values (1164) 110639
97.1%
ValueCountFrequency (%)
0 157
0.1%
0.0513 1
 
< 0.1%
0.0532 1
 
< 0.1%
0.0545 1
 
< 0.1%
0.0548 1
 
< 0.1%
0.055 1
 
< 0.1%
0.0555 1
 
< 0.1%
0.0558 1
 
< 0.1%
0.0562 1
 
< 0.1%
0.0565 2
 
< 0.1%
ValueCountFrequency (%)
0.985 1
 
< 0.1%
0.984 1
 
< 0.1%
0.983 1
 
< 0.1%
0.982 1
 
< 0.1%
0.981 2
< 0.1%
0.98 2
< 0.1%
0.979 2
< 0.1%
0.978 3
< 0.1%
0.977 1
 
< 0.1%
0.976 4
< 0.1%

energy
Real number (ℝ)

Distinct2083
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.64138276
Minimum0
Maximum1
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size890.8 KiB
2023-12-12T00:09:42.509958image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.154
Q10.472
median0.685
Q30.854
95-th percentile0.969
Maximum1
Range1
Interquartile range (IQR)0.382

Descriptive statistics

Standard deviation0.25152907
Coefficient of variation (CV)0.39216687
Kurtosis-0.52571082
Mean0.64138276
Median Absolute Deviation (MAD)0.186
Skewness-0.59700142
Sum73117.634
Variance0.063266872
MonotonicityNot monotonic
2023-12-12T00:09:42.554379image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.876 318
 
0.3%
0.937 269
 
0.2%
0.931 261
 
0.2%
0.886 258
 
0.2%
0.801 258
 
0.2%
0.948 254
 
0.2%
0.858 254
 
0.2%
0.961 254
 
0.2%
0.92 240
 
0.2%
0.981 238
 
0.2%
Other values (2073) 111396
97.7%
ValueCountFrequency (%)
0 1
 
< 0.1%
1.95 × 10-51
 
< 0.1%
2.01 × 10-513
 
< 0.1%
2.02 × 10-54
 
< 0.1%
2.03 × 10-534
< 0.1%
2.82 × 10-51
 
< 0.1%
3.05 × 10-51
 
< 0.1%
3.61 × 10-51
 
< 0.1%
4.28 × 10-53
 
< 0.1%
5.9 × 10-52
 
< 0.1%
ValueCountFrequency (%)
1 28
 
< 0.1%
0.999 100
0.1%
0.998 149
0.1%
0.997 165
0.1%
0.996 159
0.1%
0.995 229
0.2%
0.994 173
0.2%
0.993 184
0.2%
0.992 161
0.1%
0.991 200
0.2%

key
Real number (ℝ)

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3091404
Minimum0
Maximum11
Zeros13061
Zeros (%)11.5%
Negative0
Negative (%)0.0%
Memory size890.8 KiB
2023-12-12T00:09:42.590453image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q38
95-th percentile11
Maximum11
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.5599871
Coefficient of variation (CV)0.67053928
Kurtosis-1.2765712
Mean5.3091404
Median Absolute Deviation (MAD)3
Skewness-0.0085003605
Sum605242
Variance12.673508
MonotonicityNot monotonic
2023-12-12T00:09:42.620370image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
7 13245
11.6%
0 13061
11.5%
2 11644
10.2%
9 11313
9.9%
1 10772
9.4%
5 9368
8.2%
11 9282
8.1%
4 9008
7.9%
6 7921
6.9%
10 7456
6.5%
Other values (2) 10930
9.6%
ValueCountFrequency (%)
0 13061
11.5%
1 10772
9.4%
2 11644
10.2%
3 3570
 
3.1%
4 9008
7.9%
5 9368
8.2%
6 7921
6.9%
7 13245
11.6%
8 7360
6.5%
9 11313
9.9%
ValueCountFrequency (%)
11 9282
8.1%
10 7456
6.5%
9 11313
9.9%
8 7360
6.5%
7 13245
11.6%
6 7921
6.9%
5 9368
8.2%
4 9008
7.9%
3 3570
 
3.1%
2 11644
10.2%

loudness
Real number (ℝ)

Distinct19480
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-8.2589604
Minimum-49.531
Maximum4.532
Zeros0
Zeros (%)0.0%
Negative113910
Negative (%)99.9%
Memory size890.8 KiB
2023-12-12T00:09:42.658252image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-49.531
5-th percentile-18.067
Q1-10.013
median-7.004
Q3-5.003
95-th percentile-2.974
Maximum4.532
Range54.063
Interquartile range (IQR)5.01

Descriptive statistics

Standard deviation5.0293366
Coefficient of variation (CV)-0.60895517
Kurtosis5.8962782
Mean-8.2589604
Median Absolute Deviation (MAD)2.343
Skewness-2.0065419
Sum-941521.48
Variance25.294227
MonotonicityNot monotonic
2023-12-12T00:09:42.702115image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-5.662 176
 
0.2%
-4.457 90
 
0.1%
-9.336 86
 
0.1%
-7.57 77
 
0.1%
-4.034 75
 
0.1%
-8.871 74
 
0.1%
-3.725 72
 
0.1%
-4.324 70
 
0.1%
-5.08 64
 
0.1%
-12.472 64
 
0.1%
Other values (19470) 113152
99.3%
ValueCountFrequency (%)
-49.531 1
 
< 0.1%
-49.307 1
 
< 0.1%
-46.591 1
 
< 0.1%
-46.251 1
 
< 0.1%
-43.957 1
 
< 0.1%
-43.943 1
 
< 0.1%
-43.714 1
 
< 0.1%
-43.504 1
 
< 0.1%
-43.303 1
 
< 0.1%
-43.046 3
< 0.1%
ValueCountFrequency (%)
4.532 1
< 0.1%
3.156 1
< 0.1%
2.574 1
< 0.1%
1.864 1
< 0.1%
1.821 1
< 0.1%
1.795 1
< 0.1%
1.7 1
< 0.1%
1.682 1
< 0.1%
1.673 1
< 0.1%
1.416 1
< 0.1%

mode
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size890.8 KiB
1
72681 
0
41319 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters114000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 72681
63.8%
0 41319
36.2%

Length

2023-12-12T00:09:42.739229image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T00:09:42.771605image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
1 72681
63.8%
0 41319
36.2%

Most occurring characters

ValueCountFrequency (%)
1 72681
63.8%
0 41319
36.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 114000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 72681
63.8%
0 41319
36.2%

Most occurring scripts

ValueCountFrequency (%)
Common 114000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 72681
63.8%
0 41319
36.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 114000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 72681
63.8%
0 41319
36.2%

speechiness
Real number (ℝ)

Distinct1489
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.084652112
Minimum0
Maximum0.965
Zeros157
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size890.8 KiB
2023-12-12T00:09:42.806285image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0282
Q10.0359
median0.0489
Q30.0845
95-th percentile0.268
Maximum0.965
Range0.965
Interquartile range (IQR)0.0486

Descriptive statistics

Standard deviation0.10573236
Coefficient of variation (CV)1.2490222
Kurtosis28.824377
Mean0.084652112
Median Absolute Deviation (MAD)0.0165
Skewness4.647516
Sum9650.3408
Variance0.011179333
MonotonicityNot monotonic
2023-12-12T00:09:42.850640image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0323 400
 
0.4%
0.0324 376
 
0.3%
0.0322 373
 
0.3%
0.0328 363
 
0.3%
0.0295 358
 
0.3%
0.0321 352
 
0.3%
0.033 347
 
0.3%
0.0367 346
 
0.3%
0.0326 340
 
0.3%
0.0306 332
 
0.3%
Other values (1479) 110413
96.9%
ValueCountFrequency (%)
0 157
0.1%
0.0221 3
 
< 0.1%
0.0222 1
 
< 0.1%
0.0223 3
 
< 0.1%
0.0225 2
 
< 0.1%
0.0226 2
 
< 0.1%
0.0227 3
 
< 0.1%
0.0228 5
 
< 0.1%
0.0229 1
 
< 0.1%
0.023 9
 
< 0.1%
ValueCountFrequency (%)
0.965 1
 
< 0.1%
0.963 2
 
< 0.1%
0.962 6
< 0.1%
0.961 2
 
< 0.1%
0.96 3
 
< 0.1%
0.959 6
< 0.1%
0.958 6
< 0.1%
0.957 8
< 0.1%
0.956 7
< 0.1%
0.955 11
< 0.1%

acousticness
Real number (ℝ)

Distinct5061
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.31491006
Minimum0
Maximum0.996
Zeros39
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size890.8 KiB
2023-12-12T00:09:42.896385image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.000145
Q10.0169
median0.169
Q30.598
95-th percentile0.948
Maximum0.996
Range0.996
Interquartile range (IQR)0.5811

Descriptive statistics

Standard deviation0.3325227
Coefficient of variation (CV)1.0559291
Kurtosis-0.94993129
Mean0.31491006
Median Absolute Deviation (MAD)0.1675
Skewness0.72729486
Sum35899.747
Variance0.11057135
MonotonicityNot monotonic
2023-12-12T00:09:42.940085image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.995 305
 
0.3%
0.993 267
 
0.2%
0.994 266
 
0.2%
0.992 250
 
0.2%
0.991 218
 
0.2%
0.131 206
 
0.2%
0.881 204
 
0.2%
0.108 195
 
0.2%
0.107 190
 
0.2%
0.99 189
 
0.2%
Other values (5051) 111710
98.0%
ValueCountFrequency (%)
0 39
< 0.1%
1 × 10-61
 
< 0.1%
1.01 × 10-64
 
< 0.1%
1.02 × 10-61
 
< 0.1%
1.03 × 10-62
 
< 0.1%
1.04 × 10-64
 
< 0.1%
1.06 × 10-65
 
< 0.1%
1.07 × 10-64
 
< 0.1%
1.08 × 10-62
 
< 0.1%
1.09 × 10-61
 
< 0.1%
ValueCountFrequency (%)
0.996 103
 
0.1%
0.995 305
0.3%
0.994 266
0.2%
0.993 267
0.2%
0.992 250
0.2%
0.991 218
0.2%
0.99 189
0.2%
0.989 177
0.2%
0.988 150
0.1%
0.987 158
0.1%

instrumentalness
Real number (ℝ)

Distinct5346
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15604959
Minimum0
Maximum1
Zeros38763
Zeros (%)34.0%
Negative0
Negative (%)0.0%
Memory size890.8 KiB
2023-12-12T00:09:42.984620image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4.16 × 10-5
Q30.049
95-th percentile0.904
Maximum1
Range1
Interquartile range (IQR)0.049

Descriptive statistics

Standard deviation0.30955485
Coefficient of variation (CV)1.9836954
Kurtosis1.2707471
Mean0.15604959
Median Absolute Deviation (MAD)4.16 × 10-5
Skewness1.7344062
Sum17789.653
Variance0.095824204
MonotonicityNot monotonic
2023-12-12T00:09:43.027275image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38763
34.0%
3.59 × 10-5166
 
0.1%
0.895 122
 
0.1%
0.905 122
 
0.1%
0.934 121
 
0.1%
0.922 118
 
0.1%
0.911 115
 
0.1%
0.000141 115
 
0.1%
0.913 114
 
0.1%
0.9 114
 
0.1%
Other values (5336) 74130
65.0%
ValueCountFrequency (%)
0 38763
34.0%
1 × 10-632
 
< 0.1%
1.01 × 10-646
 
< 0.1%
1.02 × 10-636
 
< 0.1%
1.03 × 10-634
 
< 0.1%
1.04 × 10-650
 
< 0.1%
1.05 × 10-639
 
< 0.1%
1.06 × 10-649
 
< 0.1%
1.07 × 10-656
 
< 0.1%
1.08 × 10-647
 
< 0.1%
ValueCountFrequency (%)
1 13
< 0.1%
0.999 22
< 0.1%
0.998 6
 
< 0.1%
0.997 11
< 0.1%
0.996 4
 
< 0.1%
0.995 15
< 0.1%
0.994 4
 
< 0.1%
0.993 9
< 0.1%
0.992 11
< 0.1%
0.991 12
< 0.1%

liveness
Real number (ℝ)

Distinct1722
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.21355284
Minimum0
Maximum1
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size890.8 KiB
2023-12-12T00:09:43.070781image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0606
Q10.098
median0.132
Q30.273
95-th percentile0.681
Maximum1
Range1
Interquartile range (IQR)0.175

Descriptive statistics

Standard deviation0.1903777
Coefficient of variation (CV)0.89147821
Kurtosis4.3782683
Mean0.21355284
Median Absolute Deviation (MAD)0.051
Skewness2.1057381
Sum24345.023
Variance0.036243668
MonotonicityNot monotonic
2023-12-12T00:09:43.114593image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.108 1353
 
1.2%
0.111 1318
 
1.2%
0.109 1198
 
1.1%
0.11 1179
 
1.0%
0.105 1114
 
1.0%
0.107 1102
 
1.0%
0.103 1094
 
1.0%
0.106 1064
 
0.9%
0.112 1063
 
0.9%
0.113 1008
 
0.9%
Other values (1712) 102507
89.9%
ValueCountFrequency (%)
0 2
< 0.1%
0.00925 1
< 0.1%
0.00986 1
< 0.1%
0.0112 1
< 0.1%
0.0114 1
< 0.1%
0.0116 1
< 0.1%
0.0118 1
< 0.1%
0.0133 1
< 0.1%
0.0136 1
< 0.1%
0.0137 1
< 0.1%
ValueCountFrequency (%)
1 2
 
< 0.1%
0.997 1
 
< 0.1%
0.995 1
 
< 0.1%
0.994 3
 
< 0.1%
0.993 2
 
< 0.1%
0.992 9
< 0.1%
0.991 4
 
< 0.1%
0.99 11
< 0.1%
0.989 17
< 0.1%
0.988 17
< 0.1%

valence
Real number (ℝ)

Distinct1790
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.47406823
Minimum0
Maximum0.995
Zeros176
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size890.8 KiB
2023-12-12T00:09:43.157651image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0708
Q10.26
median0.464
Q30.683
95-th percentile0.911
Maximum0.995
Range0.995
Interquartile range (IQR)0.423

Descriptive statistics

Standard deviation0.25926106
Coefficient of variation (CV)0.54688555
Kurtosis-1.0274297
Mean0.47406823
Median Absolute Deviation (MAD)0.212
Skewness0.11507804
Sum54043.778
Variance0.0672163
MonotonicityNot monotonic
2023-12-12T00:09:43.201399image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.961 300
 
0.3%
0.304 248
 
0.2%
0.717 233
 
0.2%
0.962 230
 
0.2%
0.324 225
 
0.2%
0.963 216
 
0.2%
0.55 210
 
0.2%
0.365 205
 
0.2%
0.949 204
 
0.2%
0.202 201
 
0.2%
Other values (1780) 111728
98.0%
ValueCountFrequency (%)
0 176
0.2%
1 × 10-5129
0.1%
0.000322 1
 
< 0.1%
0.000378 1
 
< 0.1%
0.000667 1
 
< 0.1%
0.000673 1
 
< 0.1%
0.000755 1
 
< 0.1%
0.000781 1
 
< 0.1%
0.00084 1
 
< 0.1%
0.000885 1
 
< 0.1%
ValueCountFrequency (%)
0.995 1
 
< 0.1%
0.994 1
 
< 0.1%
0.993 3
< 0.1%
0.992 4
< 0.1%
0.991 3
< 0.1%
0.99 1
 
< 0.1%
0.989 1
 
< 0.1%
0.988 4
< 0.1%
0.987 2
< 0.1%
0.986 1
 
< 0.1%

tempo
Real number (ℝ)

Distinct45653
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.14784
Minimum0
Maximum243.372
Zeros157
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size890.8 KiB
2023-12-12T00:09:43.244500image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile77.3469
Q199.21875
median122.017
Q3140.071
95-th percentile175.06715
Maximum243.372
Range243.372
Interquartile range (IQR)40.85225

Descriptive statistics

Standard deviation29.978197
Coefficient of variation (CV)0.24542552
Kurtosis-0.10858061
Mean122.14784
Median Absolute Deviation (MAD)21.7025
Skewness0.23229486
Sum13924853
Variance898.69229
MonotonicityNot monotonic
2023-12-12T00:09:43.287614image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 157
 
0.1%
151.925 146
 
0.1%
95.004 95
 
0.1%
87.925 76
 
0.1%
130.594 76
 
0.1%
92.988 70
 
0.1%
125.004 70
 
0.1%
76.783 69
 
0.1%
77.321 67
 
0.1%
90.04 63
 
0.1%
Other values (45643) 113111
99.2%
ValueCountFrequency (%)
0 157
0.1%
30.2 1
 
< 0.1%
30.322 1
 
< 0.1%
31.834 1
 
< 0.1%
34.262 1
 
< 0.1%
34.821 1
 
< 0.1%
35.392 1
 
< 0.1%
35.79 1
 
< 0.1%
35.862 1
 
< 0.1%
35.928 1
 
< 0.1%
ValueCountFrequency (%)
243.372 1
 
< 0.1%
222.605 1
 
< 0.1%
220.525 1
 
< 0.1%
220.084 1
 
< 0.1%
220.081 3
< 0.1%
220.039 1
 
< 0.1%
219.971 1
 
< 0.1%
219.693 1
 
< 0.1%
219.571 1
 
< 0.1%
218.879 1
 
< 0.1%

time_signature
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size890.8 KiB
4
101843 
3
 
9195
5
 
1826
1
 
973
0
 
163

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters114000
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row4
4th row3
5th row4

Common Values

ValueCountFrequency (%)
4 101843
89.3%
3 9195
 
8.1%
5 1826
 
1.6%
1 973
 
0.9%
0 163
 
0.1%

Length

2023-12-12T00:09:43.325268image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T00:09:43.360939image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
4 101843
89.3%
3 9195
 
8.1%
5 1826
 
1.6%
1 973
 
0.9%
0 163
 
0.1%

Most occurring characters

ValueCountFrequency (%)
4 101843
89.3%
3 9195
 
8.1%
5 1826
 
1.6%
1 973
 
0.9%
0 163
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 114000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 101843
89.3%
3 9195
 
8.1%
5 1826
 
1.6%
1 973
 
0.9%
0 163
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 114000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 101843
89.3%
3 9195
 
8.1%
5 1826
 
1.6%
1 973
 
0.9%
0 163
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 114000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 101843
89.3%
3 9195
 
8.1%
5 1826
 
1.6%
1 973
 
0.9%
0 163
 
0.1%

track_genre
Categorical

HIGH CARDINALITY  UNIFORM 

Distinct114
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size890.8 KiB
acoustic
 
1000
punk-rock
 
1000
progressive-house
 
1000
power-pop
 
1000
pop
 
1000
Other values (109)
109000 

Length

Max length17
Median length11
Mean length7.0701754
Min length3

Characters and Unicode

Total characters806000
Distinct characters25
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowacoustic
2nd rowacoustic
3rd rowacoustic
4th rowacoustic
5th rowacoustic

Common Values

ValueCountFrequency (%)
acoustic 1000
 
0.9%
punk-rock 1000
 
0.9%
progressive-house 1000
 
0.9%
power-pop 1000
 
0.9%
pop 1000
 
0.9%
pop-film 1000
 
0.9%
piano 1000
 
0.9%
party 1000
 
0.9%
pagode 1000
 
0.9%
opera 1000
 
0.9%
Other values (104) 104000
91.2%

Length

2023-12-12T00:09:43.394549image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
acoustic 1000
 
0.9%
drum-and-bass 1000
 
0.9%
alternative 1000
 
0.9%
ambient 1000
 
0.9%
anime 1000
 
0.9%
black-metal 1000
 
0.9%
bluegrass 1000
 
0.9%
blues 1000
 
0.9%
brazil 1000
 
0.9%
breakbeat 1000
 
0.9%
Other values (104) 104000
91.2%

Most occurring characters

ValueCountFrequency (%)
e 73000
 
9.1%
a 68000
 
8.4%
o 67000
 
8.3%
r 57000
 
7.1%
n 50000
 
6.2%
i 47000
 
5.8%
s 44000
 
5.5%
t 43000
 
5.3%
p 39000
 
4.8%
l 39000
 
4.8%
Other values (15) 279000
34.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 772000
95.8%
Dash Punctuation 34000
 
4.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 73000
 
9.5%
a 68000
 
8.8%
o 67000
 
8.7%
r 57000
 
7.4%
n 50000
 
6.5%
i 47000
 
6.1%
s 44000
 
5.7%
t 43000
 
5.6%
p 39000
 
5.1%
l 39000
 
5.1%
Other values (14) 245000
31.7%
Dash Punctuation
ValueCountFrequency (%)
- 34000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 772000
95.8%
Common 34000
 
4.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 73000
 
9.5%
a 68000
 
8.8%
o 67000
 
8.7%
r 57000
 
7.4%
n 50000
 
6.5%
i 47000
 
6.1%
s 44000
 
5.7%
t 43000
 
5.6%
p 39000
 
5.1%
l 39000
 
5.1%
Other values (14) 245000
31.7%
Common
ValueCountFrequency (%)
- 34000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 806000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 73000
 
9.1%
a 68000
 
8.4%
o 67000
 
8.3%
r 57000
 
7.1%
n 50000
 
6.2%
i 47000
 
5.8%
s 44000
 
5.5%
t 43000
 
5.3%
p 39000
 
4.8%
l 39000
 
4.8%
Other values (15) 279000
34.6%

Interactions

2023-12-12T00:09:40.632531image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:33.613364image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:34.259853image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:34.879154image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:35.428289image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:35.997436image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:36.653872image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:37.190594image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:37.754707image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:38.325540image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:39.009571image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:39.555329image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:40.094696image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:40.673749image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:33.680867image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:34.300850image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
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2023-12-12T00:09:34.837846image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
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2023-12-12T00:09:37.147547image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:37.713045image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:38.267791image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:38.966707image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:39.513022image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:40.053593image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-12-12T00:09:40.591771image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Correlations

2023-12-12T00:09:43.431233image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Unnamed: 0popularityduration_msdanceabilityenergykeyloudnessspeechinessacousticnessinstrumentalnesslivenessvalencetempoexplicitmodetime_signature
Unnamed: 01.0000.033-0.0290.007-0.064-0.006-0.043-0.0420.100-0.0840.0270.053-0.0250.1020.0720.070
popularity0.0331.0000.0280.027-0.024-0.0030.035-0.0680.008-0.078-0.008-0.0420.0170.0890.0370.046
duration_ms-0.0290.0281.000-0.0980.1040.0140.022-0.129-0.1700.127-0.040-0.1780.0500.0110.0040.036
danceability0.0070.027-0.0981.0000.0390.0350.1120.159-0.039-0.144-0.1450.462-0.0710.1540.0850.279
energy-0.064-0.0240.1040.0391.0000.0450.7500.355-0.708-0.0350.1770.2080.2410.1160.0870.161
key-0.006-0.0030.0140.0350.0451.0000.0320.044-0.0380.005-0.0040.0330.0120.0400.2470.021
loudness-0.0430.0350.0220.1120.7500.0321.0000.232-0.534-0.2890.1110.2210.1940.1080.0450.152
speechiness-0.042-0.068-0.1290.1590.3550.0440.2321.000-0.214-0.0490.0920.0920.1150.3060.0670.085
acousticness0.1000.008-0.170-0.039-0.708-0.038-0.534-0.2141.000-0.096-0.042-0.021-0.2170.1020.1000.141
instrumentalness-0.084-0.0780.127-0.144-0.0350.005-0.289-0.049-0.0961.000-0.099-0.320-0.0050.1040.0590.067
liveness0.027-0.008-0.040-0.1450.177-0.0040.1110.092-0.042-0.0991.0000.0130.0190.0420.0290.040
valence0.053-0.042-0.1780.4620.2080.0330.2210.092-0.021-0.3200.0131.0000.0630.0690.0330.111
tempo-0.0250.0170.050-0.0710.2410.0120.1940.115-0.217-0.0050.0190.0631.0000.0400.0260.496
explicit0.1020.0890.0110.1540.1160.0400.1080.3060.1020.1040.0420.0690.0401.0000.0370.060
mode0.0720.0370.0040.0850.0870.2470.0450.0670.1000.0590.0290.0330.0260.0371.0000.028
time_signature0.0700.0460.0360.2790.1610.0210.1520.0850.1410.0670.0400.1110.4960.0600.0281.000

Missing values

2023-12-12T00:09:41.368946image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T00:09:41.570059image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T00:09:41.823330image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Unnamed: 0track_idartistsalbum_nametrack_namepopularityduration_msexplicitdanceabilityenergykeyloudnessmodespeechinessacousticnessinstrumentalnesslivenessvalencetempotime_signaturetrack_genre
005SuOikwiRyPMVoIQDJUgSVGen HoshinoComedyComedy73230666False0.6760.46101-6.74600.14300.03220.0000010.35800.715087.9174acoustic
114qPNDBW1i3p13qLCt0Ki3ABen WoodwardGhost (Acoustic)Ghost - Acoustic55149610False0.4200.16601-17.23510.07630.92400.0000060.10100.267077.4894acoustic
221iJBSr7s7jYXzM8EGcbK5bIngrid Michaelson;ZAYNTo Begin AgainTo Begin Again57210826False0.4380.35900-9.73410.05570.21000.0000000.11700.120076.3324acoustic
336lfxq3CG4xtTiEg7opyCyxKina GrannisCrazy Rich Asians (Original Motion Picture Soundtrack)Can't Help Falling In Love71201933False0.2660.05960-18.51510.03630.90500.0000710.13200.1430181.7403acoustic
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